Snowflake

A data warehouse built for the cloud

Integrate the Snowflake API with the Python API

Setup the Snowflake API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Snowflake and Python remarkably fast. Free for developers.

Run Python Code with Python API on New Row from Snowflake API
Snowflake + Python
 
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Run Python Code with Python API on Query Results from Snowflake API
Snowflake + Python
 
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New Query Results from the Snowflake API

Run a SQL query on a schedule, triggering a workflow for each row of results

 
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New Row from the Snowflake API

Emit new event when a row is added to a table

 
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Insert Multiple Rows with the Snowflake API

Insert multiple rows into a table

 
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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

 
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Insert Single Row with the Snowflake API

Insert a row into a table

 
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Overview of Snowflake

Snowflake offers a cloud database and related tools to help developers create robust, secure, and scalable data warehouses. See Snowflake's Key Concepts & Architecture.

Getting Started

1. Create a user, role and warehouse in Snowflake

Snowflake recommends you create a new user, role, and warehouse when you integrate a third-party tool like Pipedream. This way, you can control permissions via the user / role, and separate Pipedream compute and costs with the warehouse. We recommend you create a read-only account if you only need to query Snowflake.

2. Enter those details in Pipedream

  1. Visit https://pipedream.com/accounts
  2. Click the button to Connect an App
  3. Enter the required Snowflake data.

You'll only need to connect your account once in Pipedream. You can use this account to run queries against Snowflake, insert data, and more.

3. Build your first workflow

Visit [https://pipedream.com/new] to build your first workflow. Pipedream workflows let you connect Snowflake with 1,000+ other apps. You can trigger workflows on Snowflake queries, sending results to Slack, Google Sheets, or any app that exposes an API. Or you can accept data from another app, transform it with Python, Node.js, Go or Bash code, and insert it into Snowflake.

Learn more at Pipedream University.

Connect Snowflake

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import { promisify } from 'util'
import snowflake from 'snowflake-sdk'

export default defineComponent({
  props: {
    snowflake: {
      type: "app",
      app: "snowflake",
    }
  },
  async run({steps, $}) {
    const connection = snowflake.createConnection({
      ...this.snowflake.$auth,
      application: "PIPEDREAM_PIPEDREAM",
    })
    const connectAsync = promisify(connection.connect)
    await connectAsync()
    
    async function connExecuteAsync(options) {
      return new Promise((resolve, reject) => {
        connection.execute({
          ...options,
          complete: function(err, stmt, rows) {
            if (err) {
              reject(err)
            } else {
              resolve({stmt, rows})
            }
          }
        })
      })
    }
    
    // See https://docs.snowflake.com/en/user-guide/nodejs-driver-use.html#executing-statements
    const { rows } = await connExecuteAsync({
      sqlText: `SELECT CURRENT_TIMESTAMP()`,
    })
    return rows
  },
})

Overview of Python

Python API on Pipedream offers developers to build or automate a variety of
tasks from their web and cloud apps. With the Python API, users are able to
create comprehensive and flexible scripts, compose and manage environment
variables, and configure resources to perform a range of functions.

By using Pipedream, you can easily:

  • Create automated workflows that run on a specific schedule
  • Compose workflows across various apps and services
  • React to events in cloud services or form data
  • Automatically create content and notifications
  • Construct classifications and predictions
  • Analyze and react to sentiment, sentiment analysis and sentiment score
  • Connect backends to the frontend with serverless functions
  • Work with files and databases
  • Perform web requests and fetch data
  • Integrate third-party APIs into your apps
  • Orchestrate data processing tasks and pipelines
  • Create powerful application APIs with authentication and authorization
  • Design CI/CD pipelines and Continuous Delivery services
  • Connect databases like MongoDB and MySQL
  • Monitor connections and events
  • Generate alerts and notifications for corresponding events

Connect Python

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def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}